Many of today’s leading app-led businesses are highly dependent on contextualization.

Think about Uber if it didn’t have critical contextual information such as your location and the location of the taxis that are currently on shift in your area. It would be impossible for the app to send a car to collect you.

It wouldn’t be any more useful than this:

Uber without contextUber is just one example of many companies that have transformed industries by making use of contextual data such as location to offer a whole new level of service to customers.

Location-based data not only helps businesses like Uber, but also media businesses who can serve up content based on location, such as news stories specific to your local area. Or retail websites such as Autotrader, Ebay or Shpock who will feature items for sale closer to your geographic location. This benefits the user by serving up content and information that they are more likely to find useful. Importantly, it also aids the companies selling the services – likelihood of a sale is higher because of improved customer experience, and they can gain valuable insights from this data which can be fed back into their sales and marketing strategies.

So how can today’s companies make better use of context?

Most businesses have access to data which can help with this, such as knowing their location, timings of actions, their persona, purpose, and intent. But so often this data is stored in separate silos, making it hard to integrate and get the big picture.

A joined-up view of your customer is crucial if you want to excel in experience. You can overcome these silos by using a wrap-around solution that connects your silos, feeds the data into your processes, and makes customer insights available to your team.

This kind of digital innovation can not only help you respond to customers, but it can also give you a richer understanding of how they’re feeling. When your systems are connected and intelligent, you can better analyze your data. By scrutinizing multiple metrics – from your NPS (net promoter score) to your CES (customer effort score) – you gauge customer satisfaction with more accuracy.

Take Bizagi customer Old Mutual for example. The bank’s internal complexity meant their customer service was suffering due to lack of visibility of customer data. By introducing a common service layer that integrated with all their digital technologies, they could leverage customer insight and data analytics. This empowered staff both in-branch and online with a 360-degree customer view and the ability to answer questions in real time. This led to point of contact resolution being improved by over 30% and branch wait times reduced with queues nine times shorter. Their NPS was improved by an impressive 15%, proving the value of knowing customer context and information.

Old Mutual context complexity

 

Intelligent Automation for Customer Experience 

Everyone is talking about Robotic Process Automation and Artificial Intelligence. More than 40% of enterprises will create state-of-the-art digital workers by combining AI with RPA this year, according to Forbes. Integrating them into your businesses processes has multiple benefits, including end-to-end automation, freeing up employees’ time as cognitive technology completes certain tasks, and aiding customer experience.

RPA can help you to understand how customers are feeling and therefore overcome their pain-points. As PWC highlights, “By researching what customers want to see, hear, think and feel during the customer journey, RPA can be implemented at key points to help deliver a fast and intuitive overall experience – creating a whole greater than the sum of its parts.”

Artificial Intelligence can be put to good use by interrogating contextual data. This can help drive decisions about what information is relevant to the customer at that point in time. This analytical benefit can be invaluable when put to work in your CRM and e-commerce systems.

Additionally, AI can bring an element of machine learning to your processes and help to make recommendations on how to improve efficiency by learning from data. AI combined with contextualization can dramatically improve your customer experience.

 

It’s not enough anymore to deliver a service based solely on who your customer is. You also need to react to where they are and what they’re doing. In short, context is key. If you’d like to learn more about how to bring context to your customer experience, download our eBook Make Your Breakthrough in Customer Engagement. The report features global research from over 500 businesses to reveal how agile experimentation, ubiquitous connectivity, and engaging experiences are driving digital business.

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